Types of Data Structure Algorithms

Learn what are the different types of data structure algorithms with its implementation, examples and applications in real world programming.

We have enlisted and explained different types of algorithms used in data structures and have implemented them in C programming language.

What is a Data Structure?

A data structure can be viewed as a systematic way to organise data so that it can be used efficiently. The choice of an appropriate data structure can greatly affect the efficiency of any given program.

It is a logical way of storing data on your computer or hard drive which also, in a way, defines the retrieval process.

What is an Algorithm?

An algorithm is a procedure having well-defined steps for solving a particular problem. The data stored in data structures are manipulated by using different algorithms, so the study of data structures includes the study of algorithms.

Let us now have a look at different types of data structure algorithms that are extensively used to solve different computational problems.

Different Types of Data Structure Algorithms

1. Greedy Algorithm

A greedy algorithm works by taking a decision that appears the best at the moment, without thinking about the future.

This algorithm follows the problem-solving heuristic which means that a local optimum is chosen at every step in the hope of getting a global optimum.

It is not necessary that a greedy algorithm will always produce an optimal solution. The decision once taken in never reconsidered.

For finding a global optimum using a greedy algorithm, numerous steps may be required. The greedy algorithms are used to solve combinatorial problems in mathematical optimisation.

These algorithms produce good solutions for some mathematical problems, but not for every problem. There are different variations to greedy algorithms such as:

Pure greedy algorithms

Relaxed greedy algorithms

Orthogonal greedy algorithms

The different types of greedy algorithm implementations are as follows:

5. Brute Force Algorithm

The brute force algorithm is also known as exhaustive search and generate and test technique. It is a general problem solving and one of the easiest data structure algorithms.

It is the simplest way of finding the solution to a given problem. Brute – force basically means that you will have to go through all the possible solutions one after another until you find the optimum solution.

There is absolutely no relation between brute force algorithms and backtracking algorithms.

The brute – force algorithm is one of the simplest algorithms but the time that is taken by the algorithm to get an optimum solution may be comparatively higher.

So, if time is not a constraint, brute force technique is a good option. Therefore, this algorithm is used only when the problem size is small because if the problem set is large then the speed of execution will be really slow.

The different types of brute – force algorithm implementations are as follows:

6. Simple Recursive Algorithm

Recursion is a problem-solving process in which a problem is defined in terms of itself. The problem is solved by repeatedly breaking it into smaller problems, which are similar in nature to the original problems.

The smaller problems are solved and their results are applied to get the final solution to the original problem.

So, in recursive algorithms, the original problem is divided into smaller and similar problem. Recursion, therefore, proceeds by breaking a problem into smaller versions of the same problem.

The smallest version is actually the base case and it can be solved without recursion. After the base case solution is obtained, the function will stop calling itself and starts returning results.

Recursion is one of the most confusing data structure algorithms. However, if the base case is understood properly, then it becomes easier.

The different types of recursive algorithm implementations are as follows: